Day 1:
Foundations of Marketing Analytics
Introduction to marketing analytics and its role in decision-making.
Key metrics: Definitions, calculations, and interpretations.
Overview of data collection methods and tools.
Ethical considerations in data usage and privacy.
Day 2:
Data Visualization and Reporting
Principles of effective data visualization.
Hands-on training with tools like Tableau and Power BI.
Creating dashboards for real-time performance tracking.
Best practices for presenting insights to stakeholders.
Day 3:
Advanced Analytical Techniques
Predictive modeling and its applications in marketing.
Customer segmentation and targeting strategies.
A/B testing methodologies and statistical significance.
Leveraging machine learning for campaign optimization.
Day 4:
Cross-Channel Analytics and Integration
Measuring performance across digital channels (social media, email, SEO).
Integrating offline and online data for a unified view.
Attribution modeling and its impact on budget allocation.
Case studies of successful cross-channel campaigns.
Day 5:
Emerging Trends and Strategic Applications
Exploring AI and automation in marketing analytics.
Adapting to changes in consumer behavior and technology.
Future-proofing strategies for long-term success.
Capstone project: Developing a data-driven marketing plan.
